Mehran marcos sedghi biography of george

  • Generative large language models (LLMs) have been demonstrated to have gaps in diverse, cultural knowledge across the globe.
  • "Sister Act 2: Back in the Habit" (1993) is a comedy movie starring Whoopi Goldberg, who reprises her role as Las Vegas entertainer Deloris.
  • Self-Reflection Makes Large Language Models Safer, Less Biased, and Ideologically Neutral.

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    Towards Geo-Culturally Grounded LLM Generations

    Piyawat Lertvittayakumjorn⋆†, David Kinney⋆†‡,
    Vinodkumar Prabhakaran†, Donald Martin, Jr.†, Sunipa Dev†

    †Google  ‡Washington University in St. Louis
    {piyawat,vinodkpg,dxm,sunipadev}@google.com, kinney@wustl.edu

    Abstract

    Generative large language models (LLMs) have been demonstrated to have gaps in diverse, cultural knowledge across the globe. We investigate the effect of retrieval augmented generation and search-grounding techniques on the ability of LLMs to display familiarity with a diverse range of national cultures. Specifically, we compare the performance of standard LLMs, LLMs augmented with retrievals from a bespoke knowledge base (i.e., KB grounding), and LLMs augmented with retrievals from a web search (i.e., search grounding) on a series of cultural familiarity benchmarks. We find that search grounding significantly improves the LLM performance on multiple-choice benchmarks that test propositional knowl

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    Self-Reflection Makes Large Language Models Safer, Less Biased, and Ideologically Neutral

    Fengyuan Liu1+, Nouar AlDahoul1+, Gregory Eady2, Yasir Zaki1,*, Talal Rahwan1,*

    1New York University Abu Dhabi, UAE 2University of Copenhagen, Denmark
    +Joint first authors. *Joint senior authors. Correspondence: yasir.zaki@nyu.edu, talal.rahwan@nyu.edu

    Abstract

    Previous studies proposed that the reasoning capabilities of large language models (LLMs) can be improved through self-reflection, i.e., letting LLMs reflect on their own output to identify and correct mistakes in the initial responses. However, earlier experiments offer mixed results when it comes to the benefits of self-reflection. Furthermore, prior studies on self-reflection are predominantly concerned with the reasoning capabilities of models, ignoring the potential for self-reflection in safety, bias, and ideological leaning. Here, by conducting a series of experiments testing LLM’s self-reflection capabilit

  • mehran marcos sedghi biography of george

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    Volume 202: International Conference on Machine Learning, 23-29 July 2023, Honolulu, Hawaii, USA

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    Editors: Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett

    [bib][citeproc]

    Data Structures for Density Estimation

    Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal; Proceedings of the 40th International Conference on Machine Learning, PMLR 202:1-18

    [abs][Download PDF][OpenReview]

    ClusterFuG: Clustering Fully connected Graphs bygd Multicut

    Ahmed Abbas, Paul Swoboda; Proceedings of the 40th International Conference on Machine Learning, PMLR 202:19-30

    [abs][Download PDF][OpenReview]

    Generalization on the Unseen, Logic Reasoning and Degree Curriculum

    Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk; Proceedings of the 40th International Conference on Machine Learning, PMLR 202:31-60

    [abs][D